Matching NIR Face to VIS Face Using Transduction
文献类型：期刊论文
| 作者 | Zhu, Jun-Yong1,2; Zheng, Wei-Shi3,4; Lai, Jian-Huang2,3,4; Li, Stan Z.5,6
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| 刊名 | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
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| 出版日期 | 2014-03-01 |
| 卷号 | 9期号:3页码:501-514 |
| 关键词 | Heterogeneous face recognition VIS-NIR face matching transductive learning |
| 英文摘要 | Visual versus near infrared (VIS-NIR) face image matching uses an NIR face image as the probe and conventional VIS face images as enrollment. It takes advantage of the NIR face technology in tackling illumination changes and low-light condition and can cater for more applications where the enrollment is done using VIS face images such as ID card photos. Existing VIS-NIR techniques assume that during classifier learning, the VIS images of each target people have their NIR counterparts. However, since corresponding VIS-NIR image pairs of the same people are not always available, which is often the case, so those methods cannot be applied. To address this problem, we propose a transductive method named transductive heterogeneous face matching (THFM) to adapt the VIS-NIR matching learned from training with available image pairs to all people in the target set. In addition, we propose a simple feature representation for effective VIS-NIR matching, which can be computed in three steps, namely Log-DoG filtering, local encoding, and uniform feature normalization, to reduce heterogeneities between VIS and NIR images. The transduction approach can reduce the domain difference due to heterogeneous data and learn the discriminative model for target people simultaneously. To the best of our knowledge, it is the first attempt to formulate the VIS-NIR matching using transduction to address the generalization problem for matching. Experimental results validate the effectiveness of our proposed method on the heterogeneous face biometric databases. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | RECOGNITION ; IMAGES ; CLASSIFICATION ; EXTRACTION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000332459700015 |
| 公开日期 | 2015-09-22 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8037]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_生物识别与安全技术研究中心 |
| 作者单位 | 1.Sun Yat Sen Univ, Sch Math & Computat Sci, Guangzhou 510275, Guangdong, Peoples R China 2.SYSU CMU Shunde Int Joint Res Inst, Shunde, Peoples R China 3.Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510275, Guangdong, Peoples R China 4.Guangdong Prov Key Lab Computat Sci, Guangzhou 510275, Guangdong, Peoples R China 5.Chinese Acad Sci, Inst Automat, Ctr Biometr & Secur Res, Beijing 100080, Peoples R China 6.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhu, Jun-Yong,Zheng, Wei-Shi,Lai, Jian-Huang,et al. Matching NIR Face to VIS Face Using Transduction[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2014,9(3):501-514. |
| APA | Zhu, Jun-Yong,Zheng, Wei-Shi,Lai, Jian-Huang,&Li, Stan Z..(2014).Matching NIR Face to VIS Face Using Transduction.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,9(3),501-514. |
| MLA | Zhu, Jun-Yong,et al."Matching NIR Face to VIS Face Using Transduction".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 9.3(2014):501-514. |
入库方式： OAI收割
来源：自动化研究所
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